Studying small effects or subtle neuroanatomical variation requires large-scale sample size data. As a result, combining neuroimaging data from multiple datasets is necessary. Variation in acquisition protocols, magnetic field strength, scanner build, and many other non-biologically related factors can introduce undesirable bias into studies. Hence, harmonization required to remove the bias-ind...

This work addresses an important issue regarding the performance of simultaneous test procedures: the construction of multiple tests that at the same time are optimal from a statistical perspective and that also yield logically-consistent results that are easy to communicate to practitioners of statistical methods. For instance, if hypothesis A implies hypothesis B, is it possible to create opt...

This paper presents, first, a formal exploration of the relationships between information (statistically defined), statistical hypothesis testing, the use of hypothesis testing in reverse as an investigative tool, channel capacity in a communication system, uncertainty, the concept of entropy in thermodynamics, and Bayes’ theorem. This exercise brings out the close mathematical interrelationshi...

Bayes and Naive-Bayes Classifier

Different cultivars of seeds may have different properties. Therefore, distinguishing be important for seed processing and product quality. This study was aimed at revealing the usefulness innovative models developed based on selected image textures built using traditional machine algorithms cultivar classification quince seeds. The belonging to four ‘Uspiech’, ‘Leskovac’, ‘Bereczki’, ‘Kaszczen...

The main purpose of this paper is to provide a methodology for discussing the fuzzy. Bayesian system reliability from the fuzzy component reliabilities, actually we discuss on the Fuzzy Bayesian system reliability assessment based on Pascal distribution, because the data sometimes cannot be measured and recorded precisely. In order to apply the Bayesian approach, the fuzzy parameters are assume...